AIMC Topic: Machine Learning

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Artificial intelligence and machine learning in emergency medicine.

Emergency medicine Australasia : EMA
Interest in artificial intelligence (AI) research has grown rapidly over the past few years, in part thanks to the numerous successes of modern machine learning techniques such as deep learning, the availability of large datasets and improvements in ...

Estimating individualized optimal combination therapies through outcome weighted deep learning algorithms.

Statistics in medicine
With the advancement in drug development, multiple treatments are available for a single disease. Patients can often benefit from taking multiple treatments simultaneously. For example, patients in Clinical Practice Research Datalink with chronic dis...

Abnormal Low-Frequency Oscillations Reflect Trait-Like Pain Ratings in Chronic Pain Patients Revealed through a Machine Learning Approach.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Measures of moment-to-moment fluctuations in brain activity of an individual at rest have been shown to be a sensitive and reliable metric for studying pathological brain mechanisms across various chronic pain patient populations. However, the relati...

Causal Discovery Combining K2 with Brain Storm Optimization Algorithm.

Molecules (Basel, Switzerland)
Exploring and detecting the causal relations among variables have shown huge practical values in recent years, with numerous opportunities for scientific discovery, and have been commonly seen as the core of data science. Among all possible causal di...

Webcrawling and machine learning as a new approach for the spatial distribution of atmospheric emissions.

PloS one
In this study we apply two methods for data collection that are relatively new in the field of atmospheric science. The two developed methods are designed to collect essential geo-localized information to be used as input data for a high resolution e...

A review of statistical and machine learning methods for modeling cancer risk using structured clinical data.

Artificial intelligence in medicine
Advancements are constantly being made in oncology, improving prevention and treatment of cancers. To help reduce the impact and deadliness of cancers, they must be detected early. Additionally, there is a risk of cancers recurring after potentially ...

A machine-learned analysis of human gene polymorphisms modulating persisting pain points to major roles of neuroimmune processes.

European journal of pain (London, England)
BACKGROUND: Human genetic research has implicated functional variants of more than one hundred genes in the modulation of persisting pain. Artificial intelligence and machine-learning techniques may combine this knowledge with results of genetic rese...

Estimating the Temperature of Heat-exposed Bone via Machine Learning Analysis of SCI Color Values: A Pilot Study.

Journal of forensic sciences
Determining maximum heating temperatures of burnt bones is a long-standing problem in forensic science and archaeology. In this pilot study, controlled experiments were used to heat 14 fleshed and defleshed pig vertebrae (wet bones) and archaeologica...

On the use of machine learning techniques for the mechanical characterization of soft biological tissues.

International journal for numerical methods in biomedical engineering
Motivated by the search for new strategies for fitting a material model, a new approach is explored in the present work. The use of numerical and complex algorithms based on machine learning techniques such as support vector machines for regression, ...

Consistent Semantic Annotation of Outdoor Datasets via 2D/3D Label Transfer.

Sensors (Basel, Switzerland)
The advance of scene understanding methods based on machine learning relies on the availability of large ground truth datasets, which are essential for their training and evaluation. Construction of such datasets with imagery from real sensor data ho...